Pada bab ini akan dibahas kesimpulan dari hasil peneletian dan dilanjutkan dengan implikasi kebijakan yang perlu diambil berdasarkan kesimpulan tersebut. Pembahasan ditutup dengan limitasi dan saran dari penelitian ini.
6.1. Kesimpulan
Bedasarkan analisis pada bab sebelumnya, maka kesimpulan dari hasil penelitian ini antara lain sebagai berikut:
1. Hasil pengujian dengan analisis dekomposisi varian dengan basis VAR menunjukkan bahwa inflasi paling berperan dalam menjelaskan fluktuasi PMA di Indonesia dibandingkan tingkat bunga dan nilai tukar. Hal ini berarti bahwa penerapan Inflation
Targeting dimana inflasi merupakan sasaran akhir kebijakan moneter adalah layak untuk
dilanjutkan .
2. Kontribusi pengaruh moneter terhadap fluktuasi PMA semakin kuat dalam jangka panjang . Hal ini menunjukkan bahwa kebijakan moneter memiliki lag yang lama dalam memberikan dampak pada peningkatan PMA .
3. Berdasarkan analisis impulse response, guncangan pada inflasi mendapat respon paling cepat dan paling kuat direspon oleh PMA, dibandingkan oleh kurs dan tingkat bunga. 4. Meskipun moneter dalam penelitian ini berperan dalam menjelaskan fluktuasi PMA,
namun peran PMA itu sendiri jauh lebih besar . Hal ini diduga bahwa fluktuasi PMA lebih dapat dijelaskan oleh variabel riil di luar moneter.
6.2 Implikasi Kebijakan
Sesuai dengan kesimpulan dari hasil penelitian, maka implikasi kebijakan yang perlu dilakukan dalam rangka peningkatan PMA di Indonesia berkaitan dengan kebijakan moneter antara lain:
1. Dalam kerangka penciptaan stabilitas makro ekonomi untuk menciptakan fundamental yang kuat bagi perekonomian, maka stabilitas harga merupakan sasaran akhir yang harus menjadi target kebijakan moneter. Penerapan Inflation Targeting yang sudah dilakukan lebih superior dibandingkan dengan Monetary Targeting. Oleh karena itu, peletakan landasan kebijakan yang diarahkan untuk tercapainya target inflasi harus diupayakan dengan langkah yang tepat.
2. Pendekatan Interest Rate Rule atau Taylor Rule, menggunakan tingkat bunga sebagai sasaran antara untuk mencapai sasaran akhir stabilitas harga dapat diterapkan dalam kerangka Inflation Targeting, mengingat bahwa dalam jangka panjang variabel inflasi lebih berperan dalam menjelaskan fluktuasi tingkat bunga.
3. Oleh karena variabel riil diduga lebih berperan dalam menjelaskan fluktuasi PMA di Indonesia, maka faktor stabilitas politik dan keamanan, kepastian hukum, serta peningkatan pelayanan publik harus diutamakan disamping penciptaan stabilitas fundamental ekonomi, dalam rangka peningkatan PMA di Indonesia.
6.3 Limitasi.
Terdapat beberapa keterbatasan dalam penelitian ini, antara lain :
1. Penulis hanya menggunakan pendekatan taylor rule, dalam pendekatan analisis dan tidak menggunakan Money base (Mc Callum Rule) maupun State Contingent Rule sebagai perbandingan sebagaimana yang dilakukan oleh Solikin (2005).
2. Penelitian ini hanya mengkaji variabel moneter kaitannya dengan PMA, dan tidak memasukkan variabel riil. Diduga peran variabel riil lebih besar terhadap fluktuasi PMA di Indonesia, mengingat relatif kecilnya peran/kontribusi variabel moneter
6.4 Saran
Untuk lebih mengembangkan pemahaman tentang perilaku penanaman modal asing di Indonesia, disarankan kepada peneliti lain agar dapat melakukan analisis kebijakan moneter dengan beberapa pendekatan serta memasukkan variabel riil sebagai pembanding sehingga memberikan hasil yang lebih komprehensif bagi optimalisasi kebijakan moneter dalam kaitannya dengan penanaman modal asing.
DAFTAR PUSTAKA
Ball, Christopher P and Javier Rayes, 2004, “Inflation Targeting or Fear of Floating in Disguise: The Case of Mexico” in International Jurnal of Finance and Economics. January.
Ball, L. 1997. Efficient Rule for Monetary Policy, NBER Working Paper No. 5952
Bernanke, Ben S. et al. 1999. Inflation Targeting, Lessons from the International Experience, New Jersey.
Brooks, Douglas H. Et.al. 2003. “Foreign Direct Investment in Developing Asia: Trends, Effects, and Likely Issues for the Forthcoming WTO Negotiations” ERD Working Paper No. 38
Chen, David Y. 2005. “Foreign Direct Investment in the United States: Interest and Exchange Rate” in Southern Business Review
Froot, Kenneth A. 1993. “Foreign Direct Investment” in National Bureau of Economic Research. London
Froyen, Richard T. 2003. Macroeconomics, Theories and Policies, International Edition, New Jersey
Gujarati, Damodar. 2003. Basic Econometrics. First Edition, New York: Mc Grow Hill Jr, Kelly William A, and Miles James A. 1989. “Capital Structure Theory and the Fisher
Effect” in The Financial Review
Krugman and Obsfeld. 2003. International Economics, Theory and Policy. Sixth Edition. Boston
Kwan, CH. et. al. 1998. Coping with Capital Inflow in East Asia. Tokyo
Manurung, Rahardja. 2002. Pengantar Ilmu Ekonomi. Jakarta: LPFE Universitas Indonesia
Natagami, Keizo. 1980. Monetary Theory. Amsterdam: North Holland Publishing Company.
Prakosa. 2003. Pengaruh Tax Holiday terhadap PMA di Indonesia. Jurnal Ekonomi dan Moneter
Rossenberg, Michael R. 2003. Exchange Rate Determination, Models and Strategies for Exchange Rate Forecasting
Solikin. 2005. Fluktuasi Makroekonomi dan Respon Kebijakan yang Optimal di Indonesia. (Disertasi tidak dipublikasikan). Universitas Indonesia
Sudarsono, Heri. 2003. Analisis Faktor-Faktor yang Mempengaruhi Investasi di Indonesia. Jurnal Ekonomi dan Moneter
Sukirno, Sadono. 2002. Pengantar Teori Makroekonomi. Jakarta: Rajawali Press Svensson, Lars E.O. 1997. “Inflation Forecast Targeting: Implementing and Monitoring
Inflation Target” in European Economic Review
Taylor, John B. 2001.” The Role of Exchange Rate in Monetary Policy Rules” in The Amarican Economic Review
______. 1993. “Discretion versus Policy Rules in Practice” Carniege-Rochester Conferences Series on Public Policy, 39
______. 1999. Monetary Policy Rules, NBER Conference Report. Chicago: The University of Chicago Press
Warjiyo, Perry. 2004. Bank Sentral Republik Indonesia Sebuah Pengantar, Jakarta: Pusat Pendidikan dan Studi Kebanksentralan Bank Indonesia.
Wong, Ka-Fu. 2000. “Variability in the Effects on Monetary Policy in Economic Activity” in Journal of Money, Credit and Banking
______. Statistik Ekonomi dan Keuangan Indonesia, berbagai edisi, Bank Indonesia
Lampiran 1
Null Hypothesis: IHK has a unit root Exogenous: Constant
Lag Length: 0 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -1.631869 0.4625 Test critical values: 1% level -3.500669
5% level -2.892200
10% level -2.583192
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(IHK)
Method: Least Squares Date: 08/07/07 Time: 12:44 Sample (adjusted): 2 96
Included observations: 95 after adjustments
Variable Coefficient
Std.
Error t-Statistic Prob.
IHK(-1) -0.052662 0.032271 -1.631869 0.1061
C 9.573560 6.035100 1.586313 0.1161
R-squared 0.027837 Mean dependent var 0.179053 Adjusted R-squared 0.017384 S.D. dependent var 17.80905 S.E. of regression 17.65358 Akaike info criterion 8.600582 Sum squared resid 28983.33 Schwarz criterion 8.654347 Log likelihood -406.5276 F-statistic 2.662995 Durbin-Watson stat 1.927410 Prob(F-statistic) 0.106089
Lampiran 2
Null Hypothesis: SBI has a unit root Exogenous: Constant
Lag Length: 7 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -7.320046 0.0000 Test critical values: 1% level -3.506484
5% level -2.894716
10% level -2.584529
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(SBI)
Method: Least Squares Date: 08/07/07 Time: 12:45 Sample (adjusted): 9 96
Included observations: 88 after adjustments
Variable Coefficient
Std.
Error t-Statistic Prob. SBI(-1) -0.096553 0.013190 -7.320046 0.0000 D(SBI(-1)) 0.543939 0.101876 5.339206 0.0000 D(SBI(-2)) 0.158827 0.085458 1.858536 0.0668 D(SBI(-3)) -0.396336 0.050378 -7.867296 0.0000 D(SBI(-4)) 0.010499 0.065755 0.159662 0.8736 D(SBI(-5)) -0.039224 0.042491 -0.923098 0.3588 D(SBI(-6)) 0.214036 0.041384 5.171895 0.0000 D(SBI(-7)) -0.012014 0.042762 -0.280939 0.7795 C 1.138241 0.213553 5.330017 0.0000
R-squared 0.839701 Mean dependent var -0.658864 Adjusted R-squared 0.823469 S.D. dependent var 2.283164 S.E. of regression 0.959286 Akaike info criterion 2.851402 Sum squared resid 72.69817 Schwarz criterion 3.104766 Log likelihood -116.4617 F-statistic 51.72874 Durbin-Watson stat 2.093504 Prob(F-statistic) 0.000000
Lampiran 3
Null Hypothesis: PMA has a unit root Exogenous: Constant
Lag Length: 0 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -9.147729 0.0000 Test critical values: 1% level -3.500669
5% level -2.892200
10% level -2.583192
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(PMA)
Method: Least Squares Date: 08/07/07 Time: 12:48 Sample (adjusted): 2 96
Included observations: 95 after adjustments
Variable Coefficient Std. Error t-Statistic Prob. PMA(-1) -0.948233 0.103658 -9.147729 0.0000
C 479552.8 79304.86 6.046953 0.0000
R-squared 0.473627 Mean dependent var -4058.594 Adjusted R-squared 0.467968 S.D. dependent var 789908.1 S.E. of regression 576163.4 Akaike info criterion 29.38700 Sum squared resid 3.09E+13 Schwarz criterion 29.44076 Log likelihood -1393.882 F-statistic 83.68095 Durbin-Watson stat 2.004549 Prob(F-statistic) 0.000000
Lampiran 4
Null Hypothesis: KURS has a unit root Exogenous: Constant
Lag Length: 0 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -3.515261 0.0096 Test critical values: 1% level -3.500669
5% level -2.892200
10% level -2.583192
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(KURS)
Method: Least Squares Date: 08/07/07 Time: 12:55 Sample (adjusted): 2 96
Included observations: 95 after adjustments
Variable Coefficient Std. Error t-Statistic Prob. KURS(-1) -0.230812 0.065660 -3.515261 0.0007
C 2100.224 604.5366 3.474105 0.0008
R-squared 0.117287 Mean dependent var -5.736842 Adjusted R-squared 0.107796 S.D. dependent var 835.4238 S.E. of regression 789.1125 Akaike info criterion 16.20052 Sum squared resid 57910965 Schwarz criterion 16.25429 Log likelihood -767.5248 F-statistic 12.35706 Durbin-Watson stat 1.513587 Prob(F-statistic) 0.000681
Lampiran 5
Null Hypothesis: D(IHK) has a unit root Exogenous: Constant
Lag Length: 0 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -9.546797 0.0000 Test critical values: 1% level -3.501445
5% level -2.892536
10% level -2.583371
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(IHK,2)
Method: Least Squares Date: 08/07/07 Time: 13:01 Sample (adjusted): 3 96
Included observations: 94 after adjustments
Variable Coefficient Std. Error t-Statistic Prob. D(IHK(-1)) -0.991484 0.103855 -9.546797 0.0000
C 0.017922 1.849655 0.009689 0.9923
R-squared 0.497656 Mean dependent var -0.162128 Adjusted R-squared 0.492195 S.D. dependent var 25.16424 S.E. of regression 17.93214 Akaike info criterion 8.632113 Sum squared resid 29583.67 Schwarz criterion 8.686226 Log likelihood -403.7093 F-statistic 91.14134 Durbin-Watson stat 2.005407 Prob(F-statistic) 0.000000
Lampiran 6
Null Hypothesis: D(KURS) has a unit root Exogenous: Constant
Lag Length: 0 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -8.505967 0.0000 Test critical values: 1% level -3.501445
5% level -2.892536
10% level -2.583371
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(KURS,2)
Method: Least Squares Date: 08/07/07 Time: 13:02 Sample (adjusted): 3 96
Included observations: 94 after adjustments
Variable Coefficient
Std.
Error t-Statistic Prob. D(KURS(-1)) -0.860075 0.101114 -8.505967 0.0000
C 11.99547 84.44822 0.142045 0.8874
R-squared 0.440224 Mean dependent var 15.10638 Adjusted R-squared 0.434140 S.D. dependent var 1088.418 S.E. of regression 818.7482 Akaike info criterion 16.27448 Sum squared resid 61672066 Schwarz criterion 16.32859 Log likelihood -762.9004 F-statistic 72.35148 Durbin-Watson stat 1.950529 Prob(F-statistic) 0.000000
Lampiran 7
Null Hypothesis: D(PMA) has a unit root Exogenous: Constant
Lag Length: 3 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -8.542308 0.0000 Test critical values: 1% level -3.503879
5% level -2.893589
10% level -2.583931
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(PMA,2)
Method: Least Squares Date: 08/07/07 Time: 13:02 Sample (adjusted): 6 96
Included observations: 91 after adjustments
Variable Coefficient Std. Error t-Statistic Prob. D(PMA(-1)) -3.091716 0.361930 -8.542308 0.0000 D(PMA(-1),2) 1.298015 0.304829 4.258172 0.0001 D(PMA(-2),2) 0.751023 0.212298 3.537579 0.0007 D(PMA(-3),2) 0.355585 0.107086 3.320557 0.0013
C 7878.721 64772.41 0.121637 0.9035
R-squared 0.817727 Mean dependent var 2985.765 Adjusted R-squared 0.809250 S.D. dependent var 1413618. S.E. of regression 617397.2 Akaike info criterion 29.55779 Sum squared resid 3.28E+13 Schwarz criterion 29.69575 Log likelihood -1339.879 F-statistic 96.45518 Durbin-Watson stat 2.072213 Prob(F-statistic) 0.000000
Lampiran 8
Null Hypothesis: D(SBI) has a unit root Exogenous: Constant
Lag Length: 11 (Automatic based on SIC, MAXLAG=11)
t-Statistic Prob.* Augmented Dickey-Fuller test statistic -6.211474 0.0000 Test critical values: 1% level -3.511262
5% level -2.896779
10% level -2.585626
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(SBI,2)
Method: Least Squares Date: 08/07/07 Time: 13:05 Sample (adjusted): 14 96
Included observations: 83 after adjustments
Variable Coefficient Std. Error t-Statistic Prob. D(SBI(-1)) -0.352694 0.056781 -6.211474 0.0000 D(SBI(-1),2) -0.073279 0.081319 -0.901132 0.3706 D(SBI(-2),2) -0.020338 0.079141 -0.256981 0.7979 D(SBI(-3),2) -0.053230 0.072092 -0.738364 0.4628 D(SBI(-4),2) -0.201529 0.061594 -3.271913 0.0017 D(SBI(-5),2) -0.121500 0.059986 -2.025486 0.0466 D(SBI(-6),2) 0.080664 0.049350 1.634521 0.1066 D(SBI(-7),2) 0.194781 0.042363 4.597859 0.0000 D(SBI(-8),2) 0.092800 0.031841 2.914466 0.0048 D(SBI(-9),2) 0.071368 0.028239 2.527303 0.0138 D(SBI(-10),2) 0.087902 0.026742 3.287028 0.0016 D(SBI(-11),2) 0.138828 0.026457 5.247280 0.0000 C -0.002764 0.058763 -0.047037 0.9626 R-squared 0.800400 Mean dependent var 0.030241 Adjusted R-squared 0.766183 S.D. dependent var 0.985351 S.E. of regression 0.476463 Akaike info criterion 1.498054 Sum squared resid 15.89119 Schwarz criterion 1.876909 Log likelihood -49.16925 F-statistic 23.39179 Durbin-Watson stat 2.117648 Prob(F-statistic) 0.000000
Lampiran 9
VAR Lag Order Selection Criteria
Endogenous variables: DLIHK DLKURS DLPMA DSBI Exogenous variables: C
Date: 07/09/07 Time: 13:11 Sample: 1 96
Included observations: 85
Lag LogL LR FPE AIC SC HQ 0 -355.8416 NA 0.055875 8.466861 8.581809 8.513096 1 -39.39253 595.6688 4.76e-05 1.397471 1.972213* 1.628648* 2 -25.89908 24.12945 5.06e-05 1.456449 2.490984 1.872568 3 -10.33841 26.36161 5.14e-05 1.466786 2.961114 2.067847 4 15.62877 41.54749 4.12e-05 1.232264 3.186385 2.018266 5 21.32931 8.584347 5.35e-05 1.474604 3.888519 2.445548 6 39.46598 25.60472 5.25e-05 1.424330 4.298037 2.580215 7 74.65675 46.36901 3.48e-05 0.972782 4.306283 2.313610 8 90.49468 19.37818 3.71e-05 0.976596 4.769889 2.502365 9 103.9631 15.21136 4.25e-05 1.036163 5.289250 2.746874 10 140.7970 38.13390* 2.88e-05* 0.545954* 5.258834 2.441606
* indicates lag order selected by the criterion
LR: sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error
AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion
Lampiran 10
Vector Autoregression Estimates Date: 06/15/07 Time: 09:18 Sample (adjusted): 3 96
Included observations: 94 after adjustments Standard errors in ( ) & t-statistics in [ ]
DLIHK DLKURS DLPMA DSBI
DLIHK(-1) 0.941144 -0.001990 -0.370571 -1.327319 (0.03250) (0.02607) (0.26880) (1.09756) [ 28.9563] [-0.07635] [-1.37860] [-1.20934] DLKURS(-1) 0.065581 0.795018 -1.155454 8.517423 (0.08383) (0.06723) (0.69329) (2.83082) [ 0.78231] [ 11.8249] [-1.66662] [ 3.00882] DLPMA(-1) 0.011881 -0.003759 0.119139 -0.191365 (0.01258) (0.01009) (0.10408) (0.42498) [ 0.94406] [-0.37244] [ 1.14468] [-0.45030] DSBI(-1) 0.000935 -0.000293 0.004666 0.961289 (0.00075) (0.00060) (0.00619) (0.02527) [ 1.24917] [-0.48839] [ 0.75382] [ 38.0335] C -0.462535 1.930377 23.58290 -67.71227 (0.82060) (0.65813) (6.78655) (27.7105) [-0.56366] [ 2.93312] [ 3.47495] [-2.44356] R-squared 0.913003 0.627438 0.071017 0.950612 Adj. R-squared 0.909093 0.610693 0.029265 0.948393 Sum sq. resids 0.902727 0.580659 61.74387 1029.398 S.E. equation 0.100712 0.080773 0.832917 3.400922 F-statistic 233.5072 37.47157 1.700918 428.2679 Log likelihood 84.96438 105.7034 -113.6261 -245.8717 Akaike AIC -1.701370 -2.142626 2.523960 5.337695 Schwarz SC -1.566088 -2.007344 2.659241 5.472976 Mean dependent 5.134349 9.108703 12.76225 17.93138 S.D. dependent 0.334030 0.129455 0.845379 14.97067 Determinant resid covariance (dof adj.) 0.000488
Determinant resid covariance 0.000392 Log likelihood -164.8358 Akaike information criterion 3.932677 Schwarz criterion 4.473804
Kerangka Pemikiran Teorit is
Kebijakan moneter Pertumbuhan
ekonomi
Tingkat bunga Tingkat inflasi Nilai tukar
PM A Utang luar negeri Investasi (I) Pengeluaran pemerintah (G) Stabilitas ekonomi T a b u n g a n d o m e st ik